1. Field of the Invention
The present invention relates to a feature for use in automated dialog systems and more specifically, to a method and system that copies human interactions through learning and discovery.
2. Introduction
Approaches to sentence-level processing tasks such as parsing, language modeling, named-entity detection and machine translation have become increasingly data-driven and empirical, with the availability of large amounts of data. The benefits of such a trend have been that the models for these tasks can be trained to capture the distributions of the phenomena in the data. These trainable models are more robust as compared to the previously popular hand-crafted approaches.
This trend has yet to significantly impact the approaches to dialog management in dialog systems. Dialog management (both plan-based and call-flow based) have traditionally been hand-crafted and suffer the consequences of being unnatural and brittle. With the ability to record and store human-human conversations (such as in call-centers), it is anticipated that data-driven methods will influence approaches to dialog management in the near future.